| ---
|
| datasets:
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| - ZoneTwelve/Thermal-Heatmap-Source-Localization
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| tags:
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| - benchmark
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| - heatmap
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| - physics
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| - source-localization
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| - synthetic
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| license: apache-2.0
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| pretty_name: Thermal Heatmap Source Localization (ThermBench)
|
| ---
|
|
|
| # ThermBench 🔥 — Thermal Heatmap Source Localization Benchmark
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|
|
| ## 📝 Summary
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| **ThermBench** is a physics-inspired **synthetic dataset** designed to evaluate algorithms that infer **hidden thermal sources** from an observed **heat diffusion map**.
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|
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| Each data sample contains:
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| - an **observed heatmap** (matrix of values),
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| - and the **ground-truth sources**: `(row, col, intensity)`.
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|
|
| Diffusion follows inverse Manhattan distance:
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|
|
| \[
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| H(i,j) \;=\; \sum_{s=1}^{K} \frac{I_s}{d(i,j,s)+1}
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| \]
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|
|
| where \(d\) is the Manhattan distance to source \(s\).
|
|
|
| ---
|
|
|
| ## 📊 Dataset Structure
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|
|
| - **level**: Difficulty tier (`very_easy`, `easy`, `medium`, `hard`, `extreme`)
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| - **input_text**: Heatmap formatted as:
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| ```
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| N M
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| K
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| <N rows of values>
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| ```
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| - **output_text**: True source positions and intensities in format:
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| ```
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| row col intensity
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| ```
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|
|
| ### Example
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| ```json
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| {
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| "level": "easy",
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| "input_text": "5 5\n2\n10 8 6 5 4\n8 10 7 6 5\n6 7 10 7 6\n5 6 7 10 8\n4 5 6 8 10",
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| "output_text": "1 1 10.0\n5 5 10.0"
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| }
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| ```
|
|
|
| ---
|
|
|
| ## 🚀 Usage
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|
|
| ```python
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| from datasets import load_dataset
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|
|
| dataset = load_dataset(
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| "ZoneTwelve/Thermal-Heatmap-Source-Localization",
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| split="train"
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| )
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| print(dataset[0])
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| ```
|
|
|
| ---
|
|
|
| ## 🎚 Difficulty Levels
|
|
|
| - **very_easy** → 3×3 grid, 1 source
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| - **easy** → 5×5 grid, 2 sources
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| - **medium** → 10×10 grid, 3 sources
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| - **hard** → 20×20 grid, 5 sources
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| - **extreme** → 30×30 grid, 7 sources
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|
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| Each level contains 100 samples → **500 total**.
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|
|
| A fuzzy extension of ThermBench introduces noise, intensity jitter, and rounding differences to simulate real‑world sensor readings.
|
|
|
| ---
|
|
|
| ## 🔧 Intended Applications
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| - Benchmarking **inverse problem solvers**
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| - Robustness studies for optimization/AI
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| - Educational resource for algorithm development
|
|
|
| ---
|
|
|
| ## 📜 License
|
| Apache License 2.0 © ZoneTwelve
|
| |
